X-ray CT imaging systems have been widely used in fields such as medical treatment, security inspection, industrial non-destructive detection, etc. Ray sources and detectors collect a series of projection data according to a certain trajectory, and a three-dimensional spatial distribution of linear attenuation coefficients of an object to be inspected may be obtained through recovery by using an image reconstruction algorithm. A CT image reconstruction process is to recover a linear attenuation coefficient distribution from data acquired by the detectors, which is a core step of CT imaging. Currently, analytical reconstruction algorithms such as filtered back-projection, Feldkmap-Davis-Kress (FDK), etc. and iterative reconstruction methods such as Algebra Reconstruction Technique (ART), Maximum A Posterior (MAP), etc. are mainly used in practical applications.
With the increasing diversity of demands for X-ray CT imaging, the requirements for reducing a radiation dosage have become higher and higher, and the image quality which can be achieved by the reconstruction methods in the related art has approached the limit. There is a need to develop a new CT image reconstruction technique.